NOT APPLICABLE.
NOT APPLICABLE.
The present invention generally relates to a system for logging and analyzing medical diagnostic imaging system data. More particularly, the present invention relates to a system for logging and dynamically configuring performance analysis of medical diagnostic imaging system data, such as for six sigma studies.
The information gained from diagnostic imaging has applications in many fields, including medicine and manufacturing. Medical diagnostic imaging systems, such as an x-ray system, ultrasound system, magnetic resonance imaging (MRI) system, computed axial tomography (CAT) system, and the like, typically include a source and a detector. A target to be viewed, such as a human body, is arranged between the source and the detector. The source transmits a medium that travels through the target to reach the detector. As the medium travels from the source through the target, internal components of the target may affect the medium, such as by decreasing the energy of the medium to varying degrees through phenomena such as the blocking or absorption of the medium. The blocking or absorption of a medium, such as x-rays, within the target causes the received energy levels to vary. The detector receives the energy which have traveled through, or is reflected from, the target. An image of the target is generated based on the energy detected at the detector. The produced image contains light and dark regions which correspond to the varying intensity levels of the energy that passed through, or were reflected by, the target.
Medical diagnostic images produced by the above-described general types of system may be used for many purposes. For instance, internal defects in the target may be detected. Additionally, changes in internal structure or alignment may be determined. Furthermore, the image may show the presence or absence of objects in the target.
In order to help ensure that medical diagnostic images may be used reliably, it is advantageous to measure and verify the performance of a medical diagnostic imaging system. In particular, it is important to measure and verify the image quality of the medical diagnostic imaging system. Poor image quality may prevent reliable analysis of the medical diagnostic image. For example, a decrease in image contrast quality may yield an unreliable image that is not usable. Additionally, the advent of real-time imaging systems has increased the importance of generating clear, high quality images. Medical diagnostic imaging systems with poor or degraded image quality must be re-calibrated to provide a distinct and usable representation of the target.
It is also important to verify performance of a medical diagnostic imaging system for safety reasons. For example, exposure to high levels of energy may involve some health risk to humans. Because of the health risk, governmental standards are set for the use of certain medical diagnostic imaging systems. For instance, the level of x-ray energy emitted by a medical diagnostic imaging system may be measured in terms of radiation dosage. Periodic performance evaluation of medical diagnostic imaging systems ensures that the radiation dosage to which the target is exposed does not exceed regulatory standards.
Additionally, medical diagnostic imaging system performance may be monitored in order to determine which capabilities may be improved through further modification. If system parameters, such as network bandwidth or disk speed, do not meet performance specifications, performance data may be used to support changes to a medical diagnostic imaging system. Similarly, performance data may help isolate problems or defects to particular components or subsystems in a medical diagnostic imaging system. The detection of fluctuation in parameters, such as drive current, voltage, and temperature, may help to identify wear and to prevent future system failures.
Heretofore, medical diagnostic imaging systems have offered limited capabilities to carry out performance analysis. Current systems that collect medical diagnostic imaging system data must be pre-programmed with any and all desired parameter variables for which it is desirable to collect data (e.g., temperature, voltage, current, etc.). In order to change the amount or type of data collected for a medical diagnostic imaging system, a technician must manually reconfigure the system on-site or reprogram the software of the system. For example, if analysis of a first set of parameters (e.g., detector voltages and currents) indicates that the problem may be in a second set of parameters, the system must be manually reconfigured on-site. Manual reconfiguration may include rewriting the system""s diagnostic or application software to include the second set of parameters.
In addition, conventional medical diagnostic imaging systems must be pre-programmed to collect data at a preset sampling rate (e.g., every patient, every minute, every second, etc.). Parameter variable data is collected and logged at a predetermined sampling rate or frequency. The sampling rate for data collection and logging can only be changed by a technician manually reconfiguring the system on-site. For example, in order to reduce or increase the amount of data being received for analysis, the system must be manually adjusted on-site. Manual adjustment of the sampling rate for a parameter variable may include modification of the system""s diagnostic software.
On-site manual reconfiguration of the system unnecessarily complicates isolation and correction of errors in a medical diagnostic imaging system. Additionally, the necessity of on-site manual reconfiguration by a technician increases the amount of time, money, and personnel needed to perform accurate error detection.
Thus, a need has long existed for a system able to automatically log and analyze performance data for a medical diagnostic imaging system. Additionally, a need has long existed for a system that can be easily reconfigured to log and analyze different amounts or types of performance data for a medical diagnostic imaging system. Also, a need has long existed for a system that can log and analyze different characteristics of a chosen data set of a medical diagnostic imaging system. The preferred embodiments of the present invention address these needs and other concerns with past systems for analyzing medical diagnostic imaging systems.
A method and system are provided for configurable logging and analysis of performance data for a medical diagnostic imaging system. A medical diagnostic imaging system may be divided into subsystems. The subsystems include data acquisition modules for acquiring desired types of data related to the performance of an associated subsystem. The data acquisition modules acquire raw performance data (e.g., temperature, current, voltage, etc.) during the operation of the medical diagnostic imaging system. The data acquisition modules may remotely acquire the raw performance data. The raw performance data is acquired based upon a configuration file which identifies parameters associated with a desired type of performance analysis. New configuration files may be remotely downloaded to dynamically select at least one parameter for a desired type of performance analysis. Parameters in the configuration file may comprise at least one of a performance variable and a sampling rate for the performance variable.
A processing module processes the raw performance data acquired by the data acquisition modules. Data may be processed in real-time during the operation of the medical diagnostic imaging system. The processing module produces characteristic data summarizing the raw performance data. For example, the processing module may calculate trend statistics or perform statistical analyze on the raw performance data to produce characteristic data. Characteristic data may include at least one of minimum value, maximum value, mean, standard deviation and the like. An output module outputs the characteristic data identifying the performance of the medical diagnostic imaging system. The output module may output the characteristic data to at least one of a storage buffer, trending log, display, and central processing system.
These and other features of the preferred embodiments of the present invention are discussed or apparent in the following detailed description of the preferred embodiments of the present invention.